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Introducing OUI-1: the first open-weights model for Generative UI 71.7% on Generative UI Bench at 4B params. Beats Gemma 4 31B with 8× fewer active params, and scores 5.5× the base DiffusionGemma it was fine-tuned from. Methodology, weights, and full benchmark results in the blog 👇

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Rabi Shanker Guha

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77,618 görüntüleme • 2 ay önce •via X (Twitter)

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Added more types to the Generative effect skill. It now includes UI, text, and image variants. UI examples were generated with UI agent.
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Added more types to the Generative effect skill. It now includes UI, text, and image variants. UI examples were generated with UI agent.

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how small can you make a world model? we built mira mini, the first reproduction of mira: •⁠ ⁠reproduced in a week from scratch •⁠ ⁠four players, one shared rocket league match, in the browser •⁠ ⁠distilled to 364m params, weights, code, full report: all open. play it here ↓

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Introducing Jan v3, with updates to Jan Desktop v0.7.6 💛 Jan v3 is our first v3 model, a 4B base built for fine-tuning and fast local use, with stronger math and coding. This release also includes a small Jan Desktop update, starting with a UI refresh as we move toward a more unified Jan experience. Try it: - Jan v3 is available in Jan Desktop and at - Get the latest desktop app at Model: - Jan-v3-4B: - Jan-v3-4B-GGUF: Thanks Qwen for the base model and Georgi Gerganov for llama.cpp 💛
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Introducing Jan v3, with updates to Jan Desktop v0.7.6 💛 Jan v3 is our first v3 model, a 4B base built for fine-tuning and fast local use, with stronger math and coding. This release also includes a small Jan Desktop update, starting with a UI refresh as we move toward a more unified Jan experience. Try it: - Jan v3 is available in Jan Desktop and at - Get the latest desktop app at Model: - Jan-v3-4B: - Jan-v3-4B-GGUF: Thanks Qwen for the base model and Georgi Gerganov for llama.cpp 💛

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Introducing @𝚓𝚜𝚘𝚗-𝚛𝚎𝚗𝚍𝚎𝚛/𝚌𝚑𝚊𝚝 Generative UI for Slack, Teams and more → Agents reply with native cards → Tables, fields, charts and buttons → Streams in as the model writes → One catalog for every Chat SDK platform

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Bonsai 27B running locally on an iPhone in Atomic Chat! Bonsai is the first 27B-class model that fits on a phone. PrismML built it on Qwen3.6 27B with 1-bit weights. It takes 3.9GB instead of 54GB and keeps ~90% of the benchmark scores. Available now on iPhone and Android
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Bonsai 27B running locally on an iPhone in Atomic Chat! Bonsai is the first 27B-class model that fits on a phone. PrismML built it on Qwen3.6 27B with 1-bit weights. It takes 3.9GB instead of 54GB and keeps ~90% of the benchmark scores. Available now on iPhone and Android

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Microsoft TRELLIS.2 is here 🔥 • Single image → textured 3D mesh • 4B params, flow-matching transformer • Up to 1536³ resolution • Open weights, MIT licensed ⬇️ Demo available on Hugging Face
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Microsoft TRELLIS.2 is here 🔥 • Single image → textured 3D mesh • 4B params, flow-matching transformer • Up to 1536³ resolution • Open weights, MIT licensed ⬇️ Demo available on Hugging Face

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world models have their comfyui now. introducing alakazam studio, the first local, open source UI for world models. •⁠ ⁠sentence goes in => you edit the state graph => play •⁠ ⁠on a live model, yours, running in your browser •⁠ ⁠⁠apache-2.0, fully open source fork it and point it at your model 👇

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Introducing Generative UI for MCP Apps One server. Infinite interfaces. Instead of building views, define a component catalog. The AI assembles the right UI based on your API, CLI or MCP server tools. Works in Claude, ChatGPT, VS Code, Cursor and more

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generative ui for home automations!

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Tiny Recursive Models: A tiny 7M parameter model that recursively refines its answer beats LLMs 100x larger on hard puzzles like ARC-AGI We independently reproduced the paper, corroborated results, and released the weights + API access for those looking to benchmark it 🔍

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Today, we're joining Google's release of A2UI v0.9 🎉 Declarative Generative UI with your own design system. Works with any AG-UI Agent. Your agents describes UI via JSON, your frontend renders it using your components catalog like lego building blocks UI is alive and dead. CLI for agents, Generative UI for humans. Try it out: npx copilotkit@latest create my-app --framework a2ui

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1/4 Meet Qwenputer: Qwen3.5-4B with a full RISC-V CPU inside its weights, using the model's own Gated DeltaNet layers as RAM. It runs C and MicroPython in its forward passes, no external runtime. On DeepMind math: base 55–90%, base + Python tool 95–100%, Qwenputer 97.5–100%.

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I've joined CopilotKit🪁 as director of product to build generative UI! Ridiculously excited to get back to my frontend roots while staying at the forefront of agentic development. Post linked below on why I'm betting big on generative UI 🔗

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